Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-base-v2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Download openvino/openvino_model.bin from intfloat/e5-base-v2: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/intfloat/e5-base-v2/resolve/main/openvino/openvino_model.bin
- Command line
-
hf download hf://intfloat/e5-base-v2/openvino/openvino_model.bin
-
curl -L -o openvino_model.bin https://huggingface.co/intfloat/e5-base-v2/resolve/main/openvino/openvino_model.bin
436 MB
- Xet hash:
- 95eeb518c46f63aa888414f052670914e3159eab6ac3562ca17617e963ddffc3
- Size of remote file:
- 436 MB
- SHA256:
- 813bf62987ce7bf6e9a94d1ff42455376a036ff26463088ca95033d38cf4b880
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